https://github.com/krisharul26/password-strength-prediction-deployment

This repository, focus on password strength prediction. I have created an SVM model to classify whether password strength or medium or weak. After training the model, It has deployed on the Heroku platform.
https://github.com/krisharul26/password-strength-prediction-deployment

accuracy-metrics logistic-regression-classifier machine-learning python roc-curve svm-classifier xgboost-algorithm

Last synced: 8 months ago
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This repository, focus on password strength prediction. I have created an SVM model to classify whether password strength or medium or weak. After training the model, It has deployed on the Heroku platform.

• Host: GitHub
• URL: https://github.com/krisharul26/password-strength-prediction-deployment
• Owner: KrishArul26
• Created: 2021-05-15T19:02:34.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2021-07-15T08:33:46.000Z (about 4 years ago)
• Last Synced: 2025-01-04T18:25:34.352Z (9 months ago)
• Topics: accuracy-metrics, logistic-regression-classifier, machine-learning, python, roc-curve, svm-classifier, xgboost-algorithm
• Language: Jupyter Notebook
• Homepage:
• Size: 17.7 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Password-Strength-Prediction-Using Traditional ML

* This project has tried with SVM, Logistic Regression and XGBoosting ML algorithms

 ### Demo of the app: 

 

 * If wanted to see App Please click [here](https://password-strength-prediction.herokuapp.com/)

 

 ### Please Enter the value & clisk the predict button

 

 


  

   

  

   



### 📁 Data Collection

* Password strength data was collected on the Kaggle and this dataset contains 80000 amount of observation as well as two featuresn which are password and strength. This strength has three level which are low, medium and strong.

* The dataset used can be downloaded [Here](https://raw.githubusercontent.com/KrishArul26/Password-Strength-Prediction-Deployment/main/Password_strength_data.csv) 

### 🔑 Prerequisites

* All the dependencies and required libraries are included in the file [requirements.txt](https://github.com/KrishArul26/End-to-End-Deployment-Air-Quality-Index-prediction/blob/main/requirements.txt)

### 🚀 Installation

1. Clone the repo

* git clone https://github.com/KrishArul26/Password-Strength-Prediction-Deployment.git

2. Change your directory to the cloned repo

* cd Password-Strength-Prediction-Deployment

3. Create a Python virtual environment named 'test' and activate it

* pip install virtualenv

* virtualenv test

* test\Scripts\activate

4. Now, run the following command in your Terminal/Command Prompt to install the libraries required

* pip install -r requirements.txt

### 💡 Working

1. Open terminal. Go into the cloned project directory and type the following command:

* python Password_app.py

### 🔑 Results 

* This project has tried with SVM, Logistic Regression and XGBoosting ML algorithms with 80000 amount of the data and among them SVM has selected as best performance algorithom interm of ROC values.

### Logistic-Regreesion Confiusion Matrix: [Open In Colab](https://colab.research.google.com/drive/1GYQUTtwBDqSpFGk_lA2C_aMAGYCKBu2u)



   



### SVM - Confiusion Matrix



   



### XGBoosting - Confiusion Matrix



   



# Conclusion

* Among those model SVM has been selected because the SVM has a higher ROC-Value than the logistic regression model.